Informed consent is a central topic in contemporary biomedical ethics. Yet attempts to set defensible and feasible standards for consenting have led to persistent difficulties. In Rethinking Informed Consent in Bioethics Neil Manson and Onora O'Neill set debates about informed consent in medicine and research in a fresh light. They show why informed consent cannot be fully specific or fully explicit, and why more specific consent is not always ethically better. They argue that consent needs distinctive communicative transactions, by which (...) other obligations, prohibitions, and rights can be waived or set aside in controlled and specific ways. Their book offers a coherent, wide-ranging and practical account of the role of consent in biomedicine which will be valuable to readers working in a range of areas in bioethics, medicine and law. (shrink)

This article argues that an ethical framework will help to harness the potential of AI while keeping humans in control.

Over the last few decades, multiple studies have examined the understanding of participants in clinical research. They show variable and often poor understanding of key elements of disclosure, such as expected risks and the experimental nature of treatments. Did the participants in these studies give valid consent? According to the standard view of informed consent they did not. The standard view holds that the recipient of consent has a duty to disclose certain information to the profferer of consent because valid (...) consent requires that information to be understood. The contents of the understanding and disclosure requirements are therefore conceptually linked. In this paper, we argue that the standard view is mistaken. The disclosure and understanding requirements have distinct grounds tied to two different ways in which a token of consent can be rendered invalid. Analysis of these grounds allows us to derive the contents of the two requirements. It also implies that it is sometimes permissible to enroll willing participants who have not understood everything that they ought to be told about their clinical trials. (shrink)

Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or (...) a rationale for particular decisions in individual cases, some commentators regard ceding medical decision‐making to black box systems as contravening the profound moral responsibilities of clinicians. I argue, however, that opaque decisions are more common in medicine than critics realize. Moreover, as Aristotle noted over two millennia ago, when our knowledge of causal systems is incomplete and precarious—as it often is in medicine—the ability to explain how results are produced can be less important than the ability to produce such results and empirically verify their accuracy. (shrink)

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other (...) stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society. (shrink)

Book reviewed in this article: Principles of Biomedical Ethics. By Tom L. Beauchamp and James F. Childress.

Artificial intelligence (AI) is increasingly being developed for use in medicine, including for diagnosis and in treatment decision making. The use of AI in medical treatment raises many ethical issues that are yet to be explored in depth by bioethicists. In this paper, I focus specifically on the relationship between the ethical ideal of shared decision making and AI systems that generate treatment recommendations, using the example of IBM’s Watson for Oncology. I argue that use of this type of system (...) creates both important risks and significant opportunities for promoting shared decision making. If value judgements are fixed and covert in AI systems, then we risk a shift back to more paternalistic medical care. However, if designed and used in an ethically informed way, AI could offer a potentially powerful way of supporting shared decision making. It could be used to incorporate explicit value reflection, promoting patient autonomy. In the context of medical treatment, we need value-flexible AI that can both respond to the values and treatment goals of individual patients and support clinicians to engage in shared decision making. (shrink)

Background: More and more quantitative information is becoming available about the risks of complications arising from medical treatment. In everyday practice, this raises the question whether each and every risk, however low, should be disclosed to patients. What could be good reasons for doing or not doing so? This will increasingly become a dilemma for practitioners.Objective: To report doctors’ views on whether to disclose or withhold information on low risks of complications.Methods: In a qualitative study design, 37 respondents were included. (...) Focus group interviews were held with 22 respondents and individual in-depth interviews with 15.Results: Doctors have doubts about disclosing or withholding information on complication risk, especially in a risk range of 1 in 200 to 1 in 10 000. Their considerations on whether to disclose or to withhold information depend on a complicated mix of patient and doctor-associated reasons; on medical and personal considerations; and on the kind and purpose of intervention.Discussion: Even though the degree of a risk is important in a doctor’s considerations, the severity of the possible complications and patients’ wishes and competencies have an important role as well. Respondents said that low risks should always be communicated when there are alternatives for the intervention or when the patient may prevent or mitigate the risk. When the appropriateness of disclosing risks is doubtful, doctors should always tell their patients that no intervention is without risk, give them the opportunity to gather all the information they need or want, and enable them to detect a complication at an early stage. (shrink)

Interdisciplinarity at the universities is a heterogeneous phenomenon not easily described in general terms. Widespread agreement does, however, exist that interdisciplinary work can be meaningful only if it uses the established academic disciplines as its point of departure. Most of such work is aimed at the solution of complex problems, at gaining an overview of work carried out by other disciplines, or at dealing with the ethical dimension of scholarly and scientific endeavour. Despite numerous programmes for promoting interdisciplinary activities, the (...) status of interdisciplinarity at universities in Switzerland remains marginal. Interdisciplinarity faces problems at several levels. There are, however, successful strategies for dealing with all of these difficulties. Some proposals for promoting interdisciplinarity are presented as well. (shrink)